Integrating Programming and AI in Primary Education: A Systematic Review of Opportunities, Challenges, and SDG 4 Contributions
Description
This dataset is associated with the manuscript “Integrating Programming and AI in Primary Education: A Systematic Review of Opportunities, Challenges, and SDG 4 Contributions”. It synthesizes studies published between 2021 and 2025 on the integration of programming and artificial intelligence in primary education, highlighting their cognitive and socioemotional impacts, implementation challenges, and contributions to Sustainable Development Goal 4 (SDG 4). The dataset includes the reviewed references and supports future research in digital learning and AI literacy in early schooling.
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Steps to reproduce
This dataset was generated as part of a systematic review conducted according to the PRISMA 2020 guidelines. The process followed these steps: Databases searched: Scopus, Web of Science, ERIC, and ACM Digital Library. Time frame: 2021–2025. Keywords and search strings: combinations of “programming”, “coding”, “artificial intelligence”, “primary education”, and “computational thinking”. Inclusion criteria: peer-reviewed empirical studies focusing on programming or AI in primary/elementary education. Exclusion criteria: studies on secondary/higher education, theoretical papers without empirical data, non-English/Portuguese publications, and duplicates. Screening procedure: titles and abstracts were independently reviewed, followed by full-text analysis. Data extraction: information on authorship, year, country, research design, sample, tools, outcomes (cognitive, socioemotional, pedagogical), and contributions to SDG 4 was systematically coded into a spreadsheet. Synthesis: findings were analyzed across thematic categories (cognitive impact, socioemotional impact, teacher training, technical/pedagogical challenges, and contributions to educational policy and digital inclusion).